Semantic text search using embeddings. Example Python notebook from OpenAI demonstrating how to build a search engine using embeddings rather than straight up token matching. This is a fascinating way of implementing search, providing results that match the intent of the search (“delicious beans” for example) even if none of the keywords are actually present in the text.
Recent articles
- Trying out llama.cpp's new vision support - 10th May 2025
- Saying "hi" to Microsoft's Phi-4-reasoning - 6th May 2025
- Feed a video to a vision LLM as a sequence of JPEG frames on the CLI (also LLM 0.25) - 5th May 2025